Household PV Power Scheduling Based on an Improved Sparrow Search Algorithm

被引:0
|
作者
Lan, Yong -Jun [1 ]
Hu, Zhao-Long [1 ]
Zeng, Ling-Guo [2 ]
Li, Minglu [1 ]
机构
[1] Zhejiang Normal Univ, Coll Comp Sci & Technol, Jinhua 321004, Zhejiang, Peoples R China
[2] Zhejiang Normal Univ, Coll Phys & Elect Informat Engn, Jinhua 321004, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
renewable energy; power dispatching; household photovoltaic; sparrow search algorithm; OPTIMIZATION; GENERATION; MANAGEMENT;
D O I
10.1109/ICACI58115.2023.10146189
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With renewable energy development, wind and photovoltaic power generation will gradually penetrate the traditional distribution network and occupy a more important part of the distribution network To make up for the shortage of solar power generation, an important measure is to install a household photovoltaic power generation system at the user end, which is an essential part of the future distribution network structure. Users who install PV in their homes will not only be self-sufficient in electricity but will also be able to sell excess power back to the grid. This kind of distributed power directly integrated into the grid without dispatch can cause severe instability to the grid. Based on this, we propose a power dispatching model in this paper, which takes renewable energy and household photovoltaic power generation as the primary power sources of the grid. Household photovoltaic users can sell excess power to the grid while ensuring power consumption. In scheduling, we use an improved sparrow search algorithm to publish scheduling tasks based on real-time power balance so that each generator can provide the most appropriate power. By comparing the running results of the algorithm with different scheduling times and the number of prosumers, we found that when the scheduling time is different, the total cost does not change. When the number of prosumers increases, the total cost will decrease, and the efficiency of the improved algorithm remains stable.
引用
收藏
页数:6
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